Distinct dimensions of emotion in the human brain and their representation on the cortical surface.

Neuroimage

Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, Osaka, Japan; Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan; Graduate School of Medicine, Osaka University, Osaka, Japan. Electronic address:

Published: November 2020

We experience a rich variety of emotions in daily life, and a fundamental goal of affective neuroscience is to determine how these emotions are represented in the brain. Recent psychological studies have used naturalistic stimuli (e.g., movies) to reveal high dimensional representational structures of diverse daily-life emotions. However, relatively little is known about how such diverse emotions are represented in the brain because most of the affective neuroscience studies have used only a small number of controlled stimuli. To reveal that, we measured functional MRI to obtain blood-oxygen-level-dependent (BOLD) responses from human subjects while they watched emotion-inducing audiovisual movies over a period of 3 hours. For each of the one-second movie scenes, we annotated the movies with respect to 80 emotions selected based on a wide range of previous emotion literature. By quantifying canonical correlations between the emotion ratings and the BOLD responses, the results suggest that around 25 distinct dimensions (ranging from 18 to 36 and being subject-dependent) of the emotion ratings contribute to emotion representations in the brain. For demonstrating how the 80 emotion categories were represented in the cortical surface, we visualized a continuous semantic space of the emotion representation and mapped it on the cortical surface. We found that the emotion categories were changed from unimodal to transmodal regions on the cortical surface. This study presents a cortical representation of a rich variety of emotion categories, which covers many of the emotional experiences of daily living.

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Source
http://dx.doi.org/10.1016/j.neuroimage.2020.117258DOI Listing

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